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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

6mA-Finder: a novel online tool for predicting DNA N6-methyladenine sites in genomes
Haodong Xu, Ruifeng Hu, Peilin Jia, et al.
Bioinformatics (2020) Vol. 36, Iss. 10, pp. 3257-3259
Open Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

DeepBIO: an automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation and visualization analysis
Ruheng Wang, Yi Jiang, Junru Jin, et al.
Nucleic Acids Research (2023) Vol. 51, Iss. 7, pp. 3017-3029
Open Access | Times Cited: 104
Meta-i6mA: an interspecies predictor for identifying DNAN6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework
Md Mehedi Hasan, Shaherin Basith, Mst. Shamima Khatun, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 114
Deep transformers and convolutional neural network in identifying DNA N6-methyladenine sites in cross-species genomes
Nguyen Quoc Khanh Le, Quang‐Thai Ho
Methods (2021) Vol. 204, pp. 199-206
Closed Access | Times Cited: 82
Prediction of bio-sequence modifications and the associations with diseases
Chunyan Ao, Liang Yu, Quan Zou
Briefings in Functional Genomics (2020) Vol. 20, Iss. 1, pp. 1-18
Closed Access | Times Cited: 76
Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning
Haodong Xu, Peilin Jia, Zhongming Zhao
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Open Access | Times Cited: 74
Leveraging the attention mechanism to improve the identification of DNA N6-methyladenine sites
Ying Zhang, Yan Liu, Jian Xu, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Open Access | Times Cited: 63
i6mA-Caps: a CapsuleNet-based framework for identifying DNA N6-methyladenine sites
Mobeen Ur Rehman, Hilal Tayara, Quan Zou, et al.
Bioinformatics (2022) Vol. 38, Iss. 16, pp. 3885-3891
Open Access | Times Cited: 34
Deep6mAPred: A CNN and Bi-LSTM-based deep learning method for predicting DNA N6-methyladenosine sites across plant species
Xingyu Tang, Peijie Zheng, Xueyong Li, et al.
Methods (2022) Vol. 204, pp. 142-150
Closed Access | Times Cited: 30
The epigenetic roles of DNA N6-Methyladenine (6mA) modification in eukaryotes
Kou‐Juey Wu
Cancer Letters (2020) Vol. 494, pp. 40-46
Closed Access | Times Cited: 40
DNA6mA-MINT: DNA-6mA Modification Identification Neural Tool
Mobeen Ur Rehman, Kil To Chong
Genes (2020) Vol. 11, Iss. 8, pp. 898-898
Open Access | Times Cited: 38
Critical evaluation of web-based DNA N6-methyladenine site prediction tools
Md Mehedi Hasan, Watshara Shoombuatong, Hiroyuki Kurata, et al.
Briefings in Functional Genomics (2020) Vol. 20, Iss. 4, pp. 258-272
Closed Access | Times Cited: 37
i6mA-Vote: Cross-Species Identification of DNA N6-Methyladenine Sites in Plant Genomes Based on Ensemble Learning With Voting
Zhixia Teng, Zhengnan Zhao, Yanjuan Li, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 17
Integration of Bioinformatic Tools in Functional Analysis of Genes and Their Application in Disease Diagnosis
Jaspreet Kaur, Simran Jit, Mansi Verma
(2025), pp. 29-71
Closed Access
Dr. Kinase: predicting the drug-resistance hotspots of protein kinases
Shaofeng Lin, Chao Tu, Ruifeng Hu, et al.
Nucleic Acids Research (2025)
Open Access
HD-6mAPred: a hybrid deep learning approach for accurate prediction of N6-methyladenine sites in plant species
Huimin Li, Wei Gao, Yi Tang, et al.
PeerJ (2025) Vol. 13, pp. e19463-e19463
Open Access
Research Progress in Predicting DNA Methylation Modifications and the Relation with Human Diseases
Chunyan Ao, Lin Gao, Liang Yu
Current Medicinal Chemistry (2021) Vol. 29, Iss. 5, pp. 822-836
Closed Access | Times Cited: 22
Identification of DNA modification sites based on elastic net and bidirectional gated recurrent unit with convolutional neural network
Bin Yu, Yaqun Zhang, Xue Wang, et al.
Biomedical Signal Processing and Control (2022) Vol. 75, pp. 103566-103566
Closed Access | Times Cited: 13
MGF6mARice: prediction of DNA N6-methyladenine sites in rice by exploiting molecular graph feature and residual block
Mengya Liu, Zhan-Li Sun, Zhigang Zeng, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 3
Closed Access | Times Cited: 13
DeepVISP: Deep Learning for Virus Site Integration Prediction and Motif Discovery
Haodong Xu, Peilin Jia, Zhongming Zhao
Advanced Science (2021) Vol. 8, Iss. 9
Open Access | Times Cited: 17
I-DNAN6mA: Accurate Identification of DNA N6-Methyladenine Sites Using the Base-Pairing Map and Deep Learning
Xueqiang Fan, Bing Lin, Jun Hu, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 3, pp. 1076-1086
Closed Access | Times Cited: 7
6mA-Pred: identifying DNA N6-methyladenine sites based on deep learning
Qianfei Huang, Wenyang Zhou, Fei Guo, et al.
PeerJ (2021) Vol. 9, pp. e10813-e10813
Open Access | Times Cited: 15
SoftVoting6mA: An improved ensemble-based method for predicting DNA N6-methyladenine sites in cross-species genomes
Zhaoting Yin, Jianyi Lyu, Guiyang Zhang, et al.
Mathematical Biosciences & Engineering (2024) Vol. 21, Iss. 3, pp. 3798-3815
Open Access | Times Cited: 2
Identification of 6-methyladenosine sites using novel feature encoding methods and ensemble models
Nashwan Alromema, Muhammad Taseer Suleman, Sharaf J. Malebary, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
MetaDegron: multimodal feature-integrated protein language model for predicting E3 ligase targeted degrons
Mengqiu Zheng, Shaofeng Lin, Kunqi Chen, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access | Times Cited: 2
A convolution based computational approach towards DNA N6-methyladenine site identification and motif extraction in rice genome
Chowdhury Rafeed Rahman, Ruhul Amin, Swakkhar Shatabda, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 14
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